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Are Basel III requirements up to the task? Evidence from bankruptcy prediction models

Pierre Durand, Gaëtan Le Quang and Arnold Vialfont
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Pierre Durand: Université Paris Est Créteil, ERUDITE, 94010 Créteil Cedex, France
Gaëtan Le Quang: Univ Lyon, Université Lumière Lyon 2, GATE UMR 5824, F-69130 Ecully, France
Arnold Vialfont: Université Paris Est Créteil, ERUDITE, 94010 Créteil Cedex, France

No 2308, Working Papers from Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon

Abstract: Using a database comprising US bank balance sheet variables covering the 2000-2018 period and the list of failed banks as provided by the FDIC, we run various models to exhibit the main determinants of bank default. Among these models, Logistic Regression, Random Forest, Histogram-based Gradient Boosting Classification and Gradient Boosting Classification perform the best. Relying on various machine learning interpretation tools, we manage to provide evidence that 1) capital is a stronger predictor of default than liquidity, 2) Basel III capital requirements are set at a too low level. More precisely, having a look at the impact of the interaction between capital ratios (the risk-weighted ratio and the simple leverage ratio) and the liquidity ratio (liquid assets over total assets) on the probability of default, we show that the influence of capital on this latter completely outweighs that of liquidity, which is in fact very limited. From a prudential perspective, this questions the recent stress put on liquidity regulation. Concerning capital requirements, we provide evidence that setting the risk-weighted ratio at 15% and the simple leverage ratio at 10% would significantly decrease the probability of default without hampering banks'activities. Overall, these results therefore call for strengthening capital requirements while at the same time releasing the regulatory pressure put on liquidity.

Keywords: Basel III; capital requirements; liquidity regulation; bankruptcy prediction models; statistical learning; classification (search for similar items in EconPapers)
JEL-codes: C44 G21 G28 (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-ban, nep-big, nep-cba, nep-cfn, nep-fmk and nep-rmg
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